Freeform Source Mask Co-optimization Lithography
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Solution Overview
Problem
Current lithographic processes face challenges in simultaneously optimizing illumination sources and masks for low k1 lithography, requiring extensive computational resources and time to achieve optimal results, while existing methods often rely on constrained optimization techniques that do not allow for free-form optimization or simultaneous source and mask adjustment.
Innovation Solution
A method that enables direct computation of the gradient of a cost function for simultaneous optimization of illumination sources and masks, allowing for free-form optimization without constraints, and incorporating sub-resolution assist features to improve manufacturability, thereby speeding up the convergence and improving the process window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If constrained optimization techniques are used for source and mask optimization, then manufacturability is improved, but optimization freedom and convergence speed are reduced
Solution Approach 1:
The patent applies preliminary action by performing free-form optimization without manufacturability constraints first to achieve fast convergence and discover the full process window, then subsequently applying manufacturability constraints as a second stage. This allows the optimization to benefit from unconstrained freedom initially, then refine the solution for manufacturability without sacrificing the convergence speed achieved in the first stage.
2Productivity
If free-form optimization without constraints is used, then optimization freedom and convergence speed are improved, but manufacturability may be compromised
Solution Approach 1:
The patent performs free-form optimization as a preliminary step before applying manufacturability constraints, allowing fast convergence to establish the full process window. The unconstrained optimization quickly identifies optimal source and mask configurations, which then serve as the starting point for subsequent constrained optimization that ensures manufacturability.
Solution Approach 2:
The patent dynamically adjusts the optimization approach by transitioning from unconstrained free-form optimization to constrained optimization. This dynamic switching allows the system to benefit from the speed of unconstrained optimization initially, then adapt to enforce manufacturability constraints in a second stage, combining the advantages of both approaches.
3Manufacturing precision
If extensive computational resources are allocated for simultaneous source and mask optimization, then optimization accuracy is improved, but computational time and resource requirements increase
Solution Approach 1:
The patent performs a preliminary free-form optimization step that requires significant computational resources to achieve high accuracy and discover the full process window. This initial computationally intensive step establishes the optimal source and mask configurations, which then serve as the starting point for subsequent refinement with manufacturability constraints, reducing the need for extensive additional computation.
Solution Approach 2:
The patent maintains continuity of useful action by using the results from the free-form optimization as the starting point for constrained optimization. This continuous approach ensures that the computationally expensive calculations performed in the first stage are not repeated, but rather built upon, maintaining optimization accuracy while reducing total computational time.
Data Source
AI summary
The present disclosure relates to lithographic apparatuses and processes, and more particularly to tools for optimizing illumination sources and masks for use in lithographic apparatuses and processes. According to certain aspects, the present disclosure significantly speeds up the convergence of the optimization by allowing direct computation of gradient of the cost function. According to other aspects, the present disclosure allows for simultaneous optimization of both source and mask, thereby significantly speeding the overall convergence. According to still further aspects, the present disclosure allows for free-form optimization, without the constraints required by conventional optimization techniques.